AI Expert

We’re opening the position of an AI Expert who can combine deep technical expertise in Artificial Intelligence with excellent communication and leadership skills. As the AI Expert, you will play a pivotal role in project-related, client-facing, and internal initiatives – from supporting pre-sales activities and designing AI solutions for new projects to contributing to projects, developing proof-of-concept prototypes, and driving best practices in AI across the organization. You will work closely with cross-functional teams (Engineers, Data Scientists, Project Managers) to lead the development of AI systems and ensure their successful delivery into production. The ideal candidate is self-motivated and autonomous, able to take ownership of complex projects, and passionate about mentoring others and advancing our company’s AI capabilities to the next level.

Responsibilities:

• Pre-Sales Collaboration: Work with business development and client teams during pre-sales to identify opportunities and expose our expertise. Assist in technical discussions, requirement gathering, and proposal development to craft AI-driven solutions that meet client needs. This includes providing architectural guidance and estimating effort for AI projects in the proposal stage
• AI Solution Design & Project Kickoff: Take the lead in designing AI-based solutions for new projects, focusing on scalable and adaptable architectures. Define project scopes and technical approaches, and set up initial project structure to ensure successful launches. Collaborate with stakeholders to translate business requirements into technical plans and roadmaps.
• Prototype Development: Develop proof-of-concept (POC) models and prototype applications to demonstrate the potential of AI solutions to clients. Use experimentation to validate ideas and showcase how AI/ML techniques (e.g., predictive modeling, computer vision, NLP, generative AI) can solve specific business problems.
• Technical Leadership in Delivery: Provide hands-on technical leadership throughout the AI project lifecycle – from data exploration and model training to evaluation and deployment. Ensure that best practices in model development, validation, and deployment (MLOps) are followed for all projects. Oversee the integration of AI models into production systems, working closely with software engineers to optimize performance and scalability.
• AI Expertise Development: Drive AI knowledge-sharing and expertise across the company. Guide other engineers and data scientists on AI best practices, code quality, and project implementation. Organize and conduct technical talks, workshops, and internal training sessions to foster a culture of continuous learning in AI. Act as the go-to AI subject matter expert within the organization, nurturing a community of practice around Machine Learning and Data Science.
• Leadership & Innovation: Stay up-to-date with the latest trends and advancements in AI/ML (e.g. modern approaches and protocols, frameworks, cloud AI services, etc.). Evaluate emerging technologies such as generative AI techniques (LLMs, RAG, agents) and assess how they can be incorporated into our solutions. Encourage innovation by prototyping with new tools and approaches, and guide the team in exploring new possibilities.
• Quality Assurance: Ensure technical excellence in all AI deliverables. Participate in code and design reviews for AI components to verify they meet the highest quality standards and follow best practices. Troubleshoot and resolve complex technical issues in AI projects, ensuring robustness and reliability of solutions delivered to clients.
• Client Engagement: Act as a key technical expert for clients during project delivery. Communicate complex AI concepts and project progress in clear, non-technical terms to non-technical client stakeholders . Build trust with clients by providing expert advice, managing expectations, and ensuring that the AI solutions delivered truly add value to their business.
• Drive strategic planning, critically evaluate significant business opportunities and risks, and guide the organization through complex decision-making processes that shape long-term success.
• Strategically manage customer relationships, proactively identify long-term partnership opportunities, and ensure customer success by aligning solutions with broader business and strategic objectives.
• Conduct in-depth technical interviews for candidates, assessing their technical skills and fit with organizational objectives.

• Foster a collaborative and innovation-driven team environment, supporting technical excellence and continuous improvement.

  
  Requirements:

• Proven extensive and hands-on experience (approximately 5+ years) in software engineering and machine learning development, including a track record of delivering or architecting AI solutions in real-world projects
• Experience working in a client-facing or consulting environment
• Expert programming skills in Python and extensive experience with machine learning libraries/frameworks such as TensorFlow, Keras, PyTorch, and Scikit-learn for developing AI/ML models
• Solid understanding of software engineering principles (version control, testing, agile development) as applied to AI projects
• Strong foundation in traditional Machine Learning algorithms (e.g., regression, decision trees, clustering) as well as deep learning techniques (neural networks, CNNs/RNNs, etc.)
• Hands-on experience in end-to-end model development: data preprocessing, feature engineering, model training/tuning, and evaluation on real and synthetic datasets
• Experience deploying Machine Learning models into production environments
• Familiarity with containerization and orchestration tools (Docker, Kubernetes) for scalable deployment of ML services
• Experience with cloud platforms (Azure preferred; AWS or Google Cloud also acceptable) for model deployment and scaling of AI solutions
• Proficiency in MLOps practices and tools to streamline the ML lifecycle from development to production (this includes using continuous integration/continuous deployment (CI/CD) pipelines for ML, model versioning, monitoring, and automated testing)
• Familiarity with tools like MLflow, Kubeflow, or Azure ML for managing experiments and deployments
• Experience with implementing AI security/guardrails and cost optimization of AI systems
• Experience with Generative AI technologies, Agentic AI, and modern AI paradigms – for example, working with large language models (LLMs) and implementing Retrieval-Augmented Generation (RAG) pipelines for enhanced information retrieval
• Knowledge and experience of LLM fine-tuning for improving AI system performance
• Knowledge of building AI-driven agents (conversational or autonomous agents that utilize LLMs) and familiarity with relevant frameworks (LangChain, LangGraph, LLamaIndex, and others)
• Excellent communication skills to be able to explain complex AI concepts in clear terms and tailor the message to different audiences (Developers, business stakeholders, Clients)
• Strong presentation and writing skills to conduct tech talks, produce documentation, and contribute to proposals
• Demonstrated leadership in mentoring teams or influencing cross-functional groups
• Ability to work autonomously and self-direct in a fast-paced environment
• A proactive mindset with strong problem-solving abilities, critical thinking, and creativity in designing innovative AI solutions
• Ability to take initiative with minimal supervision, managing projects from concept to completion while meeting high-quality standards
• A Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field
• English level – Upper-Intermediate or higher

Will be a plus:

• Experience working in a client-facing or consulting environment
• Experience in Computer Vision (e.g., image processing, object detection, OpenCV or relevant deep learning models), Natural Language Processing (e.g. speech recognition, text classification, text-to-SQL), Reinforcement learning, and multimodal AI architectures
• Experience with deploying on-premises LLMs
• Experience building agentic solutions with low-code platforms
• Experience implementing Knowledge Graphs

We offer:

• Remote-first work model with flexible working hours (we provide all equipment)
• Comfortable and fully equipped offices in Lviv and Rzeszów
• Competitive compensation with regular performance reviews
• 18 paid vacation days per year + all state holidays
• 12 days of paid sick leave per year without a medical certificate + extra paid leave for blood donation
• Medical insurance with an affordable family coverage option
• Mental health program which includes free and confidential consultations with a psychologist
• English, German, and Polish language courses
• Corporate subscription to learning platforms, regular meetups and webinars
• Friendly team that values accountability, innovation, teamwork, and customer satisfaction
• Inclusive environment where everyone feels valued and treated equally. We proudly partner with VeteranHub to support Ukrainian veterans
• We are committed to supporting Ukraine and actively participate in charity initiatives